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Tool is being activelty miantained. This tool is considered complete. Bugs will be fixed, but no new features will be added 

Integrated Genome Browser

The Integrated Genome Browser (IGB, pronounced Ig-Bee) is a fast, flexible, and free desktop genome browser. First developed at Affymetrix in 2001 to support visual analytics of genome tiling arrays, IGB provides an advanced, highly customizable environment for exploring and analyzing large-scale genomic data sets.

Using IGB, you can:

  • View your RNA-Seq, ChIP-chip or ChIP-seq data alongside genome annotations and sequence.
  • Investigate alternative splicing, regulation of gene expression, epigenetic modifications of DNA, and other genome-scale questions.
  • View results from aligning short-read sequences onto a target genome, identify SNPs, and check alignment quality.
  • Copy and paste genomic sequences for further analysis into other tools, such as primer design and promoter analysis tools.
  • Create high-quality images for publication in a variety of formats.

 

IGB features

IGB lets you view results from your own experiments or computational analyses alongside public domain gene annotations, sequences, and genomic data sets, thus making it easier for you to determine how your experiments agree or disagree with current thinking and models of genomic structure.

Some features IGB offers include:

  • Animated zooming. Most genome browsers implement "jump zooming" only, in which you click a zoom button (or other type of control) and then wait for the display to re-draw. In IGB, zooming is animated, allowing you to easily and quickly adjust the zoom level as needed without losing track of your location.
  • Simple Data Sharing System - QuickLoad. IGB implements a very simple, easy-to-use system for sharing data called QuickLoad. You can use the QuickLoad system to set up a Web site you can use to share your data with colleagues, reviewers, and the public.
  • Draggable graphs. You can display genome graphs data (e.g., "bar" and "wiggle" files) alongside and even on top of reference genome annotations, thus making it easier to see how your experimental results match up to the published reference genome annotations. You can reset your graphs to "floating" and click-drag them over annotations to compare your results with annotations and others' experiments.
  • Edge-matching across tracks. When you click an item in the display, the edges of other items in the same or different tracks with identical boundaries light up, highlighting interesting similarities or differences across gene models, sequence reads, or other features.
  • Integration with local and remote external data sources. IGB can load data from a variety of sources, including Distributed Annotation Servers, QuickLoad servers, ordinary Web sites, and local files.
  • Intron-trimming sliced view. In many species, introns are huge when compared to the exonic (coding) regions of genes. IGB provides a Sliced View tab that trims uninformative regions from introns.
  • Web-controls. IGB can be controlled from a web browser or any other program capable of sending HTTP requests. Via IGB links, you can create Web pages that direct IGB to scroll to a specific region and load data sets from local files or servers.
  • Scripting. IGB understands a simple command language that allows users to write simple scripts directing IGB to show a genome, zoom and scroll to specific regions, and other functions.
  • Open source. All development on IGB proceeds via a 100% open source model. The license allows developers to incorporate IGB (and its components) into new applications.
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Institution: UNC @ Charlotte

GraphiteLifeExplorer

The GraphiteLifeExplorer modeling tool allows to build 3D molecular assemblies of proteins and DNA from Protein Database (PDB) files. Atomic DNA can be modeled from scratch or reconstructed from simulation.

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Institution: Fourmentin-Guilbert Scientific Foundation & Inria

The LifeExplorer initiative aims at providing a multiscale modelisation of a complete bacteria.

One software is currently available: GraphiteLifeExplorer

Biopython KGML module

The Biopython KGML and KEGG modules provide a programmatic interface for downloading, modifying and rendering visualisations of KEGG database pathways at publication quality. The KEGG module provides support for KEGG's REST API, and the KGML module provides parsing support for the KGML exchange format, and control over pathway element visual properties (colour, size, labelling, etc.).

 

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Institution: James Hutton Institute

GenomeDiagram

GenomeDiagram is a module written for the Python high-level programming language, providing a straightforward interface for programmatic generation of publication-quality vector, raster and streamed images. Images constructed by the package can represent very large amounts of biological information, and are designed with comparative genomics in mind, visualising elements ordered in relation to a reference sequence in either linear or circular representations.

GenomeDiagram is a module of the Biopython bioinformatics libraries for Python, and uses the ReportLab backend for rendering images. 

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Institution: James Hutton Institute

Sequence logo viewer

Web-based sequence logo viewer

Developed for the BioVis 2012 Redesign Contest, this tool provides a sequence logo using glyph-based approaches to aid interpretation.

This can be deployed using an easy to use JavaScript library that uses Raphael.js to render visualization of one or more sequence logos.

It supports DNA, RNA, and amino acid sequences.


Cite this work

E. Maguire, P. Rocca-Serra, S.-A. Sansone, and M. Chen, Redesigning the sequence logo with glyph-based approaches to aid interpretation, In Proceedings of EuroVis 2014, Short Paper (2014)

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CMView

The Contact Map View (CMView) allows an integration of rich contact map analysis with 3D visualization using PyMol. CMView provides functions for contact map calculation from structure, basic editing, visualization in contact map and 3D space and structural comparison with different built-in alignment methods. A unique feature is the interactive refinement of structural alignments based on user selected substructures.

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Institution: Max Planck Institute for Molecular Genetics, Berlin

PedVis

Public genealogical databases are becoming increasingly populated with historical data and records of the current population's ancestors. As this increasing amount of available information is used to link individuals to their ancestors, the resulting trees become deeper and more dense, which justifies the need for using organized, space-efficient layouts to display the data. Existing layouts are often only able to show a small subset of the data at a time. As a result, it is easy to become lost when navigating through the data or to lose sight of the overall tree structure. On the contrary, leaving space for unknown ancestors allows one to better understand the tree's structure, but leaving this space becomes expensive and allows fewer generations to be displayed at a time. In this work, we propose that the H-tree based layout be used in genealogical software to display ancestral trees. We will show that this layout presents an increase in the number of displayable generations, provides a nicely arranged, symmetrical, intuitive and organized fractal structure, increases the user's ability to understand and navigate through the data, and accounts for the visualization requirements necessary for displaying such trees. Finally, user-study results indicate potential for user acceptance of the new layout.

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Institution: The University of Utah

NN-tanglegram

Motivation: In systematic biology, one is often faced with the task of comparing different phylogenetic trees, in particular in multigene analysis or cospeciation studies. One approach is to use a tanglegram in which two rooted phylogenetic trees are drawn opposite each other, using auxiliary lines to connect matching taxa. There is an increasing interest in using rooted phylogenetic networks to represent evolutionary history, so as to explicitly represent reticulate events, such as horizontal gene transfer, hybridization or reassortment. Thus, the question arises how to define and compute a tanglegram for such networks. Results: In this article, we present the first formal definition of a tanglegram for rooted phylogenetic networks and present a heuristic approach for computing one, called the NN-tanglegram method.
We compare the performance of our method with existing tree tanglegram algorithms and also show a typical application to real biological datasets. For maximum usability, the algorithm does not require that the trees or networks are bifurcating or bicombining, or that they are on identical taxon sets. Availability: The algorithm is implemented in our program Dendroscope 3, which is freely available from www.dendroscope.org.

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Institution: Center for Bioinformatics (ZBIT), Tübingen University, Sand 14, 72076 Tübingen, Germany; ; Institut des Sciences de l’Evolution Montpellier (ISEM), CNRS UMR 5554, Université Montpellier II, Montpellier, France

ArkMAP

ArkMAP is a desktop application to draw and align genetic and genomic maps, retrieved from remote data sources or loaded as local files. Maps can be retrieved from our public map database ArkDB or from any Ensembl data source (i.e. Ensembl and Ensembl Genomes). By using the JEnsembl API, maps can be drawn for any release version of any of the thousands of species present in Ensembl data sources, allowing not only inter-specific comparisons, but also comparisons between different versions/revisions of assembled genomes. Maps can be aligned by relating identical or synonymous markers across maps, or through the gene homology/orthology relationship data stored in the Ensembl Compara databases, allowing ready visualization of regions of conserved synteny between species. The map drawing canvas is highly configurable, supports interactive exploration of maps, markers and relationships and allows export of publication quality graphics.

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Institution: University of Edinburgh

GenotypeChecker

GenotypeChecker is a desktop software tool for assisting data cleansing. The application identifies likely data errors in pedigree/genotype data sets by performing an inheritance-checking algorithm for each marker across the pedigree, and highlights inconsistently inherited genotypes in an exploratory user interface. By ‘masking’ suspect datapoints and rechecking inheritance consistency, erroneous datapoints can be confirmed and cleansed from the data set. The software, examples and documentation are freely available at http://bioinformatics.roslin.ac.uk/genotypechecker.

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Institution: The University of Edinburgh

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